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Publishing Language: Chinese

Trajectory and influencing factors of fasting blood glucose fluctuations in patients with type 2 diabetes mellitus in community

Yueyao XU1,2Huiyan JIAO3Meng NIE1,2Zhiquan YUAN2Na WU2Chengying LI2Long WU2Yonghong WU3Li ZHONG4Yafei LI2Jingyuan YANG1( )
Key Laboratory of Environmental Pollution Monitoring and Disease Control of Ministry of Education, Faculty of Epidemiology and Health Statistics, School of Public Health, Guizhou Medical University, Guiyang, Guizhou Province, 550025
Department of Epidemiology, Faculty of Military Preventive Medicine, Army Medical University(Third Military Medical University), Chongqing, 400038
Shuangbei Community Health Service Center of Shapingba District, Chongqing, 400032
Cardiovascular Disease Center, the Third Affiliated Hospital of Chongqing Medical University, Chongqing, 401120, China
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Abstract

Objective

To construct trajectory models of fasting blood glucose fluctuations in type 2 diabetes mellitus(T2DM)patients in community, and analyze the influencing factors of the trajectory of glucose fluctuation in different categories.

Methods

A retrospective cohort study was carried out on 769 T2DM patients who had health records and been involved in the diabetic management in Shuangbei Community Health Service Center of Shapingba District, Chongqing from 2012 to 2019. Group-based trajectory modelling(GBTM)was employed to identify and construct the fluctuation trajectory of fasting blood glucose in the patients. BIC, AvePP and other evaluation indicators were used to select the optimum subgroup number model. Then the differences in demographic characteristics, health status, medical history, lifestyle, medication compliance, etc were compared among different categories. Multinomial logistic regression model was constructed to explore the influencing factors of different fluctuation trajectories.

Results

The 769 T2DM subjects were divided into 3 groups of different fluctuation trajectories by GBTM, that is, low-level steady, high-level falling, and medium-level rising groups. Multinomial logistic regression analysis indicated that the patients with a history of hypertension and not taking medication were less likely to be assigned into the high-level falling group than into the low-level steady group, indicating that their high glucose level was not predisposed to a progressive decline(OR=0.50, 95%CI: 0.28~0.90, P=0.021; OR=0.13, 95%CI: 0.03~0.56, P=0.006). However, the subjects who occasionally or not exercised, consumed alcohol or abstained from alcohol were more likely to be assigned into the high-level falling group(OR=2.02, 95%CI: 1.15~3.55, P=0.014; OR=2.32, 95%CI: 1.16~4.63, P=0.017). When compared with the patients with regular medication, those with intermittent medication were more likely to be assigned into the medium-level rising group(OR=6.02, 95%CI: 2.86~12.66, P<0.001).

Conclusion

There are different trajectories of dynamic changes in fasting glucose for T2DM patients. History of hypertension, medication adherence, frequency of exercise, and alcohol consumption may be associated with different trajectories of blood glucose fluctuations.

CLC number: R195.4; R446.122; R587.1 Document code: A

References

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Journal of Army Medical University
Pages 786-793

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Cite this article:
XU Y, JIAO H, NIE M, et al. Trajectory and influencing factors of fasting blood glucose fluctuations in patients with type 2 diabetes mellitus in community. Journal of Army Medical University, 2023, 45(8): 786-793. https://doi.org/10.16016/j.2097-0927.202209169

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Received: 19 September 2022
Revised: 16 November 2022
Published: 30 April 2023
© 2023 Journal of Army Medical University